We used established architectures for segmentation and pose estimation. For the garment segmentation task, we trained U-Net++ [1]} [2]} from scratch on the DeepFashion dataset [3]}.
It is important for the segmentation module to precisely separate the source garment from the body, so that the reference garment can be placed at the correct location.
Otherwise the segmentation process could lead to artifacts in the form of holes or a visible outline around the garment. These artifacts were sometimes present in the U-Net++ segmentation results.
